Noometry

Model comparison

Command R vs Kimi K2.7 Code

Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 31.4 on the Noometry Index. Command R costs 6.5× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

Last verified . 0 shared benchmarks.

Command R Cohere

31.4

Rank #272 Confirmed

Kimi K2.7 Code Moonshot AI

43.3

Rank #94 Confirmed

Summary

  • The widest gap is in reasoning, where Kimi K2.7 Code leads 39.0 to 13.8.
  • Command R is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
  • Kimi K2.7 Code accepts more context: 262K tokens versus 128K.

Side by side

Command RKimi K2.7 Code
ProviderCohereMoonshot AI
Noometry Index31.443.3
Released2024-08-302026-06-12
WeightsOpenOpen
Context window128K262K
Max output4K262K
Input $ / M tokens$0.15$0.95
Output $ / M tokens$0.60$4
Results tracked2919

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Category by category

Coding Kimi K2.7 Code leads

Command R: 29.3 (#306), Kimi K2.7 Code: 42.9 (#95)

BenchmarkCommand RKimi K2.7 Code
DeepSWE—30.5%
FrontierCode—30.1%
LMArena WebDev—1473
SciCode—47.5%
WeirdML—54.1%
BigCodeBench Instruct37.1%—
LiveBench Coding17.9%—
LMArena Coding1169—
BigCodeBench Complete45.2%—
ALE-Bench—886.23

Agentic & Tool Use Not comparable

Command R: —, Kimi K2.7 Code: 24.0 (#122)

BenchmarkCommand RKimi K2.7 Code
APEX-Agents—37.6%
GBAEval—0.9%
Vending-Bench 2—5,083

Reasoning Kimi K2.7 Code leads

Command R: 13.8 (#331), Kimi K2.7 Code: 39.0 (#61)

BenchmarkCommand RKimi K2.7 Code
SimpleBench—57.9%
CritPt—10%
Chess Puzzles—21%
LiveBench Reasoning21.9%—
LMArena Hard Prompts1164—
DTBench46.4%—
LiveBench Data Analysis33.3%—
LMCA9.2%—
Surface Evolver Bench—48.8%
Epoch Capabilities Index—149.97
LiveBench27.5%—

Math Kimi K2.7 Code leads

Command R: 28.0 (#246), Kimi K2.7 Code: 52.9 (#48)

BenchmarkCommand RKimi K2.7 Code
FrontierMath (Tiers 1-3)—54%
FrontierMath Tier 4—12.2%
OTIS Mock AIME 2024-2025—95.6%
LiveBench Math19.4%—
LMArena Math1155—

Knowledge Kimi K2.7 Code leads

Command R: 31.0 (#221), Kimi K2.7 Code: 53.5 (#57)

BenchmarkCommand RKimi K2.7 Code
GPQA Diamond—87.9%
SimpleQA Verified—36.5%
LMArena Expert1138—
MMLU65.2%—

Multilingual Not comparable

Command R: 35.7 (#245), Kimi K2.7 Code: —

BenchmarkCommand RKimi K2.7 Code
LMArena Non-English1174—
LMArena Chinese1182—
LMArena French1162—
LMArena German1176—
LMArena Japanese1143—
LMArena Korean1163—
LMArena Russian1174—
LMArena Spanish1151—

Instruction Following Not comparable

Command R: 58.1 (#261), Kimi K2.7 Code: —

BenchmarkCommand RKimi K2.7 Code
LiveBench Instruction Following55.6%—
LMArena Instruction Following1167—

Long Context Not comparable

Command R: 36.3 (#231), Kimi K2.7 Code: —

BenchmarkCommand RKimi K2.7 Code
LMArena Longer Query1198—

Writing & Preference Not comparable

Command R: 38.2 (#254), Kimi K2.7 Code: —

BenchmarkCommand RKimi K2.7 Code
LMArena Text1187—
LMArena Creative Writing1170—
LMArena Multi-Turn1163—
LiveBench Language16.7%—

Frequently asked questions

Is Command R better than Kimi K2.7 Code?

Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 31.4 on the Noometry Index. Command R costs 6.5× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

Which is cheaper, Command R or Kimi K2.7 Code?

Command R is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.

Is Command R or Kimi K2.7 Code better for coding?

Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 29.3 in the Noometry coding category.

Which has the bigger context window?

Kimi K2.7 Code does, with 262K tokens against 128K.

How many benchmarks do Command R and Kimi K2.7 Code share?

0 benchmarks have published results for both models. Command R has 29 scored results on Noometry and Kimi K2.7 Code has 19.

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